LET-REMA-LC1802
Statistics and Experimental Methods II
Course infoSchedule
Course moduleLET-REMA-LC1802
Credits (ECTS)3
Category-
Language of instructionEnglish
Offered byRadboud University; Faculty of Arts; Graduate School;
Lecturer(s)
Coordinator
dr. M.B. Goudbeek
Other course modules lecturer
Lecturer
dr. M.B. Goudbeek
Other course modules lecturer
Contactperson for the course
dr. M.B. Goudbeek
Other course modules lecturer
Examiner
dr. M.B. Goudbeek
Other course modules lecturer
Academic year2023
Period
PER 3  (29/01/2024 to 07/04/2024)
Starting block
PER 3
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesNo
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
At the end of this course the student is able 
 
  • to choose and carry out appropriate statistical analysis for research questions involving continuous and categorical data (e.g. factorial ANOVA, repeated measures ANOVA, multiple regression, logistic regression)to investigate data for violations of the underlying assumptions for each analysis
  • to provide sound interpretation of such analyses and report their results accurately and accessibly
  • to reflect critically on different statistical methods and procedures
  • to get a deeper understanding of null hypothesis testing and its role in scientific inquiry
  • to be aware and understand phenomena such as questionable research practices, publication bias, and scientific misconduct and to To get acquainted with current solutions to these problems
Content

The course offers a mixture of research methodology, research design and statistical data analysis. We will look at different aspects of the research cycle, with an emphasis on strengthening the research and analytical skills of the student.

The student will acquire basic skills in using the statistical software package R. The design and statistical analysis of several research methods will be analyzed in detail. In addition, several recent topics in the field of methodology and statistics (replication, null hypothesis significance testing, confidence intervals, effect sizes, data management, research ethics) will be touched upon.

 

Articles

  1. Gigerenzer, G. (2018). Statistical rituals: The replication delusion and how we got there. Advances and Methods and Practices in Psychological Science, 1, 198-218.
  2.  McShane, B. B., Gal, D., Gelman, A., Robert, C., & Tackett, J. L. (2019). Abandon statistical significance. The American Statistician, 73, 235-245.
  3. Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E. J., Berk, R., ... & Johnson, V. E. (2018). Redefine statistical significance. Nature human behaviour, 2, 6-10.
  4. Calin-Jageman, R. J., & Cumming, G. (2019). The new statistics for better science: Ask how much, how uncertain, and what else is known. The American Statistician, 73, 271-280.
  5. Ho, J., Tumkaya, T., Aryal, S., Choi, H., & Claridge-Chang, A. (2019). Moving beyond P values: data analysis with estimation graphics. Nature methods, 16, 565-566.
  6. Francis, G. (2012). The psychology of replication and replication in psychology. Perspectives on Psychological Science, 7, 585-594.
  7.  Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant. Psychological Science, 22, 1359-1366.
  8. Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2018). False-positive citations. Perspectives on Psychological Science, 13, 255-259.
  9. Steegen, S., Tuerlinckx, F., Gelman, A., & Vanpaemel, W. (2016). Increasing transparency through a multiverse analysis. Perspectives on Psychological Science, 11, 702-712.
  10. Simonsohn, U, Simmons, J. P. and Nelson, L. D. (2020). Specification curve analysis. Nature Human Behaviour, 4, 1208-1214
Level

Presumed foreknowledge

Test information
Two take home assignments, each with 10% weight
One final written exam, 80%
Specifics

Required materials
Book
Field, Z., Miles, J., & Field, A. (2012). Discovering statistics using R. Discovering Statistics Using R, 1-992.
Articles
Selected articles

Instructional modes
Lecture/ Seminar

Tests
Assignment I
Test weight20
Test typeProject
OpportunitiesBlock PER 3, Block PER 4

Minimum grade
5,5

Assignment II
Test weight20
Test typeProject
OpportunitiesBlock PER 3, Block PER 4

Minimum grade
5,5

Written exam
Test weight60
Test typeWritten exam
OpportunitiesBlock PER 3, Block PER 4

Minimum grade
5,5